Paper Info
Title
AVSS2011 demo session: Real-time human detection using fast contour template matching for visual surveillance
Abstract
Achieving accurate pedestrian detection for practically relevant scenarios in real-time is an important problem for many applications, while representing a major scientific challenge at the same time. We present a human detection framework which efficiently computes pedestrian-specific shape and motion cues and combines them in a probabilistic manner to infer the location and occlusion status of pedestrians viewed by a stationary camera. The articulated pedestrian shape is represented by a set of sparse contour templates, where fast template matching against image features is carried out using integral images built along oriented scan-lines. The motion cue is obtained by employing a non-parametric background model using the YCbCr color space. Given the probabilistic output from the two cues the spatial configuration of hypothesized human body locations is obtained by an iterative optimization scheme taking into account the depth ordering and occlusion status of individual hypotheses. The method achieves fast computation times even in complex scenarios with a high pedestrian density. The framework and the validity of the approach will be demonstrated on various datasets with different scene complexity, such as pedestrian density and illumination conditions.
Year
DOI
Venue
2011
10.1109/AVSS.2011.6027393
AVSS
Keywords
Field
DocType
visual surveillance,probabilistic manner,articulated pedestrian shape,pedestrian density,accurate pedestrian detection,computes pedestrian-specific shape,human detection framework,occlusion status,contour template,motion cue,real-time human detection,human body location,avss2011 demo session,high pedestrian density,template matching,real time
Modalities,Template matching,Automatic summarization,Computer vision,Smart environment,Active vision,Kinematics,Computer science,Artificial intelligence,Haptic technology,Robotics
Conference
Citations 
PageRank 
References 
1
0.35
0
Authors
3
Name
Order
Citations
PageRank
Csaba Beleznai136718.96
Michael Rauter2172.56
Dan Shao321.74